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Pneumatic Tires, Structure-Process-Properties Relationships. How will you contribute? Do you have proven skills in data analysis, machine learning, as well as in mathematical and computational modelling? You
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Job Description Are you passionate about leveraging IoT, machine learning, and optimization to make energy districts and communities more sustainable? We are looking for a highly motivated and
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Embedded AI, Edge AI, TinyML, and AIoT, that can be documented by a publication record in relevant venues. Solid understanding of state-of-the-art embedded machine learning techniques. Experience in system
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. Responsibilities include working with digital signal processing, advanced filtering techniques, dynamic feature extraction, time-domain and frequency-domain analysis, signal fusion and machine learning to enhance
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Communication, Singal Processing, Low Power Electronics, Wireless Sensing, Low-Power System Design, Machine Learning & Edge Inference, Underwater acoustic communication. Furthermore, you have a proven record of
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-assembly mechanisms, identifying robust experimental signatures of collective properties, exploring practical applications, and utilizing artificial intelligence and machine learning to aid in this process
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Experience with molecular biology techniques and cell culture Willingness to learn new techniques and skills Ability to independently design and conduct experiments Willingness to think critically A passion
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to quickly learn a workflow management system). Applicants should submit CV including the list of publications; copy of the PhD diploma (notarial certification not required) or a letter from the PhD supervisor
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position from 01.10.2025 of a Postdoc Position at the Research Group Data Mining and Machine Learning at the Faculty of Computer Science, University of Vienna under the supervision of Prof. Claudia Plant
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qualification, you must hold a PhD degree (or equivalent) in computer science, computer engineering, or electrical engineering. Hardware design in a hardware description language such as Chisel, VDHL, or Verilog